Probability Plotting for Estimating Time-to-Payment Characteristics for Collections on Accounts Receivable.
The article focuses on introducing probability plotting as a tool for obtaining time-to-paying information. Markov Chain's description of accounts receivable behavior provides a valuable insight into better methods of managing accounts receivable. Probability plotting shares the same role and should be regarded as a complementary rather than a competitive technique. However, both methods have certain advantages, disadvantages and assumptions which are, for the most part different. These differences are important and furnish some guidance in determining whether a method is applicable in a given situation. M.L. Shooman indicated that Markov models work wet and have much appeal as long as the transition probabilities are constant over time. When the probabilities become time dependent, however, the Markov method breaks down, except in a few special cases. When the transition probabilities are not constant over time, a Markovian assumption is violated; but, the plotting approach is still valid and, therefore appears to have broader applicability.